If other non-Android-based TV manufacturers follow, this will have a much bigger impact on the spread (and cost) of scraping than either Anubis or Cloudflare.
Giant cookie banner says "Do not sell my personal information" + "switch the toggle to opt out".
Which is it? Am I switching the toggle to opt out of selling my personal information or am I switching it to opt out of NOT selling my personal information?
I shouldn't have to read a paragraph of fine print to tell if they are intentionally using a dark pattern or merely incapable of composing a simple declarative sentence.
It's a shame, because it looks like an interesting book.
Given all the recent press about bun rewriting 500k lines of zig into rust at a cost of $165K tokens of Fable in an 11 day sprint, would be super interested to hear about your experience and approach.
The advantage of their dataset is it's large enough that you have a statistical number of PR's, allowing you to treat the average cost of Python PR's vs the average cost of C# costs (or etc.) as statistically meaningful.
I wish they'd do a follow-on post drilling into the impact of the programming language on cost-per-task, specifically looking at cost to complete tasks in mainstream strongly typed languages (eg. C#, TypeScript) vs dynamic languages (eg. Python, JavaScript). Does the additional verbosity of the language help or hurt cost per task?
I was on my phone, so all I saw was a generic Safari error message. I think it was site not found, but I don't recall. I'm able to see it now, but am coming in through a different network provider in case that matters.
Also, not to be an apologist, but I trust you realize that "the way they handle US sanctions by blocking everybody from entire countries" is how US companies are required by law to act. Not all do act that way, of course, but almost any that have enough overseas customers to matter do, because they have enough overseas customers to need to be aware of those laws.
This reads like a nation state driven influence operation focused on feeding propaganda into LLM's and search engines (need to read towards the end to get to that part).
It's reasonable to expect stories the real local press finds discussion worthy (because they are both false and relevant to the local press) are an effective way of using the local press to throw more link strength at their own site.
>GitHub is extremely insistent its employees maximally use AI for internal development
Or it could be that GitHub saw a 14x increase in commit volume last year[0], and we've concomitantly seen its reliability fall of a cliff in the last year or so. Given that Microsoft is leasing additional space on AWS(!)[1] to handle the additional commit volume, my personal money is on commit volume growth being a bigger issue than internal use of AI.
Internal use of AI may have been an issue. Commit volume growth may have been an issue. Unless one has direct knowledge of their infrastructure issues, claiming to know is quite literally making exactly the "they are vegan, their illness must be caused by their veganism" argument the GP commenter was talking about.
>Walt Disney Company is the most successful at monetizing human nostalgia.
Coca-Cola has a much larger market cap than Disney, and the Coca-Cola brand is very intentionally a nostalgia-driven, golden age, remember the good times brand.
It's great that you understand the chart. Yellow being more optimal than green is very far from intuitive to the rest of us. We read green then yellow then red as a sign of DECREASING fit. And a bunch of blues next to that green to red progression reads as "no data" or "not relevant" or something.
It's great that you have the data. I'm sure that took a lot of time to obtain. Spending a few more percent of your total time making the presentation of the data intuitive to others is almost certainly the highest ROI thing you can do at this point, if you want your site to be useful enough to get enough visitors to pay for the cost of acquiring the data.
Feel free to tell me that red is the lowest Pareto value and that's why you made the frontier red, or whatever. I'll still respond that the details of the presentation matters enormously to adoption, and the current presentation is very far from optimally intuitive to those of us who didn't personally develop the data.
Calculations like this article neglect the far more common case where the liquidity event, if it ever happens, is years in the future, much longer than average employment times.
Companies used to go from garage to IPO rapidly. Now a decade from founding to IPO is not uncommon. Unless the employee plans on committing their life to the startup that just hired them, they will most likely move on somewhere else before that decade-later liquidity event happens.
When they leave, they have to spend after-tax $ to buy non-liquid shares of a still-high-volitility pre-IPO company, because almost all options have a 90 day exercise clause. If they were early enough that their shares are 409a valued at pre-seed valuation, that might make sense. If they are a significant employee, the kind of employee the company most wants to retain, and their shares are valued at Series B or C, that tends to be a very big check they'd need to write to their former employer to turn those options into non-liquid shares that may well end up at zero valuation, all at a time when they no longer have any ability to help the company succeed.
The original motivation for offering options was to encourage employees to stay, but what happens is the precise moment the company most wants those options to do their thing and retain the key employee is the moment when the employee starts doing the above calculation, realizing the company is years from IPO, it's still risky even if it looks promising, and the options are actually worth zero unless the employee either (a) stays at the company for a decade or (b) pays back a non-trivial fraction of their takehome pay to buy a risky illiquid asset. The employee realizes neither of those scenarios are likely to happen, so boom the moment when the company wants the options to drive retention ends up being the moment when the employee realizes the options are not just worthless, they could actually have a negative EV if exercised. Suddenly those options aren't very effective at retaining the employee.
There was a time when options had value like the OP suggests, because the timescales were shorter. Today, not so much. Yes, outliers happen, but in general they don't.
If you're not aware of "sync rights", it's probably worth reading up on given your interests. There is an entire specialization of music copyright law focused solely on synchronization of music to visuals. The good news is that studios almost never obtain this set of rights to the music they publish (because historically there wasn't enough money in it to justify negotiating for them).
One of the links in Schneier's article makes a credible sounding case that Anthropic is using open source vulnerabilities as a shakedown operation.
When the model finds a vulnerability, it also finds a fix. Anthropic only shares the vulnerability with the Open Source maintainer, not the fix. Paying customers get fixes, confirming that the model does generate fixes for the vulnerabilities.
Sharing the vulnerabilities but not the fixes does sound like a shakedown operation.